First Post

There’s been recent suggestion that more dams should be built to safegaurd against future droughts. Setting aside the question of where a new dam would be built (most appropriate locations have been utilised already), the thing that often seems to be forgotten is that most of our dams are currently storing more air than water. So how many dams have we built in Australia? Here’s a timline in R.

library(tidyverse)

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## ✔ readr   1.3.1           ✔ forcats 0.4.0

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library(sf)

## Warning: package 'sf' was built under R version 3.5.2

## Linking to GEOS 3.6.1, GDAL 2.1.3, PROJ 4.9.3

library(gganimate)

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library(lubridate)

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if(!requireNamespace("devtools")) install.packages("devtools")

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devtools::install_github("dkahle/ggmap", force=TRUE)

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library(ggmap)

## Google's Terms of Service: https://cloud.google.com/maps-platform/terms/.

## Please cite ggmap if you use it! See citation("ggmap") for details.

dams <-  readxl::read_excel("Dams-Australia-2010-v1.xls", sheet = "Australia") %>%
  janitor::clean_names() %>% slice(-c(1:2)) %>% unite("use", contains("purpose"), sep = ", ")

## New names:
## * `` -> ...1
## * `` -> ...4
## * `` -> ...8
## * DAM -> DAM...11
## * DAM -> DAM...12
## * … and 5 more problems

dams <- read_sf("kx-australian-dams-and-water-storages-SHP/australian-dams-and-water-storages.shp")
dams <- dams %>% mutate(DAM_DATE = ymd(DAM_DATE, truncated = 2)) %>% filter(!is.na(DAM_DATE))

## Warning: 1 failed to parse.

dams <- cbind(dams, sf::st_coordinates(dams))
dams <- dams %>% arrange(DAM_DATE) %>%
  mutate(n_dams=row_number())

all_years <- data.frame(DAM_DATE = seq(from=min(dams$DAM_DATE, na.rm=TRUE), to=as.Date(cut(Sys.Date(), "year")), by="year"))
dams <- left_join(all_years, dams, by="DAM_DATE") %>% arrange(DAM_DATE) %>%
  mutate(Year = year(DAM_DATE)) %>% fill(DAM_DATE:n_dams)

register_google(key="AIzaSyDZUXiRXRLl0qTdJSus6Cg_hGFdu5wZOio")

library(ggmap)
oz_map <- get_map(location = 'Australia', zoom = 4, source = 'google', maptype="satellite")

## Source : https://maps.googleapis.com/maps/api/staticmap?center=Australia&zoom=4&size=640x640&scale=2&maptype=satellite&language=en-EN&key=xxx

## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Australia&key=xxx

n_years <- nrow(distinct(dams, Year))


dams_in_time <-
  ggmap(oz_map) +
  geom_point(data = dams, aes(x=X, y=Y, group = seq_along(Year), size = CAPACITY), colour = "red", alpha=0.5) +
  transition_reveal(Year, keep_last = TRUE) +
  labs(title = "Large Dams in Australia", 
       subtitle = 'Year: {frame_along},  Number of Dams: {dams$n_dams[dams$Year == frame_along][1]}',
       size = expression("Capacity (10"^3*"m"^3*")"))

dams_in_time <- animate(plot = dams_in_time, 
                        nframes = n_years, 
                        fps=2, 
                        device="png", 
                        height = 500, 
                        width =500, 
                        )



anim_save("oz_dams_in_time.gif")

dams_in_time